Update Image Augmentation.py

Image Augmentation.py

@@ -1,2 +1,101 @@
 import streamlit as st
-st.write("Hi Welcome")
+import cv2
+import numpy as np
+from io import BytesIO
+from PIL import Image
+import base64
+from fpdf import FPDF
+
+
+def rotate_image(image, angle):
+    (h, w) = image.shape[:2]
+    center = (w // 2, h // 2)
+    rotation_matrix = cv2.getRotationMatrix2D(center, angle, 1.0)
+    rotated_image = cv2.warpAffine(image, rotation_matrix, (w, h))
+    return rotated_image
+
+
+def add_noise(image):
+    s_vs_p = 0.5
+    amount = 0.02
+    noisy_image = image.copy()
+    num_salt = np.ceil(amount * image.size * s_vs_p)
+    num_pepper = np.ceil(amount * image.size * (1.0 - s_vs_p))
+    coords = [np.random.randint(0, i - 1, int(num_salt)) for i in image.shape[:2]]
+    noisy_image[coords[0], coords[1], :] = 255
+    coords = [np.random.randint(0, i - 1, int(num_pepper)) for i in image.shape[:2]]
+    noisy_image[coords[0], coords[1], :] = 0
+    return noisy_image
+
+
+def blur_image(image, kernel_size):
+    blurred_image = cv2.GaussianBlur(image, (kernel_size, kernel_size), 0)
+    return blurred_image
+
+
+def translate_image(image, tx, ty):
+    translation_matrix = np.float32([[1, 0, tx], [0, 1, ty]])
+    height, width = image.shape[:2]
+    translated_image = cv2.warpAffine(image, translation_matrix, (width, height))
+    return translated_image
+
+
+def download_image(image, file_format):
+    pil_image = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
+    buffer = BytesIO()
+    pil_image.save(buffer, format=file_format.upper())
+    buffer.seek(0)
+    b64 = base64.b64encode(buffer.read()).decode()
+    href = f'<a href="data:file/{file_format};base64,{b64}" download="augmented_image.{file_format}">Download {file_format.upper()} File</a>'
+    return href
+
+
+def download_pdf(image):
+    pdf = FPDF()
+    pdf.add_page()
+    pil_image = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
+    buffer = BytesIO()
+    pil_image.save(buffer, format="JPEG")
+    buffer.seek(0)
+    pdf.image(buffer, x=10, y=10, w=190)
+    pdf_output = BytesIO()
+    pdf.output(pdf_output, "F")
+    pdf_output.seek(0)
+    b64 = base64.b64encode(pdf_output.read()).decode()
+    href = f'<a href="data:application/octet-stream;base64,{b64}" download="augmented_image.pdf">Download PDF</a>'
+    return href
+
+
+st.title("Image Augmentation Tool")
+
+# File upload
+uploaded_file = st.file_uploader("Upload an Image", type=["jpg", "png", "jpeg"])
+if uploaded_file:
+    image = Image.open(uploaded_file)
+    image = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+
+    st.write("### Select Transformations to Apply:")
+    rotate = st.checkbox("Rotate (45 degrees)")
+    noise = st.checkbox("Add Noise")
+    blur = st.checkbox("Blur (5x5 Kernel)")
+    translate = st.checkbox("Translate (50 pixels right and down)")
+
+    if st.button("Apply Transformations"):
+        transformed_image = image.copy()
+
+        if rotate:
+            transformed_image = rotate_image(transformed_image, 45)
+        if noise:
+            transformed_image = add_noise(transformed_image)
+        if blur:
+            transformed_image = blur_image(transformed_image, 5)
+        if translate:
+            transformed_image = translate_image(transformed_image, 50, 50)
+
+        st.image(cv2.cvtColor(transformed_image, cv2.COLOR_BGR2RGB), caption="Transformed Image", use_column_width=True)
+
+        st.markdown("### Download Transformed Image:")
+        st.markdown(download_image(transformed_image, "jpg"), unsafe_allow_html=True)
+        st.markdown(download_image(transformed_image, "png"), unsafe_allow_html=True)
+        st.markdown(download_pdf(transformed_image), unsafe_allow_html=True)